Many on-line businesses have thrived providing services and products, and facilitating customer decision-making by enabling customers and even non-customers to publish their opinions about products, services, suppliers of products and services, and purchasers of products and services. Amazon.com is one well-known example of a company using this business model. Amazon enables the users of its web portal to publish product reviews and product ratings. Another well-known example of review- and rating-based business model is eBay.com. This company enables an on-line marketplace where participants—both buyers and sellers—can rate each other based on the transactions conducted in that marketplace. Similarly, Nextag.com enables the users of its website to leave reviews and ratings for both sellers and products. Other examples of such services abound.
A large number of bad or even neutral ratings can be a kiss of death for a market participant, product, or service. On eBay, for example, buyers and sellers tend to shun those participants who have accumulated more than a small percentage of ratings that are less than “positive.” It follows that even marginal participants have mostly good ratings. At the same time, it is practically impossible to maintain an unblemished record after having participated in a reasonable number of transactions: mistakes, disagreements, misunderstandings, and frustrated expectations all take place on occasion.
For many market participants, products, and services, large numbers of reviews and ratings are available. Indeed, for quite a few market participant, products, and services, ratings and reviews number in the thousands and even in the tens of thousands. Again, such reviews are likely to be overwhelmingly positive. When a consumer attempts to evaluate the reputation of a market participant based on the ratings and reviews, the consumer may need to sift through a large number of reviews to get to the negative review or reviews. This problem arises because the reviews are listed chronologically. The consumer may need to view page after page of positive ratings and reviews before finding a few negative or neutral ratings and reviews. Yet it is the negative (or less than positive) ratings that are likely to be most significant for evaluating trustworthiness. A similar problem exists when searching through certain product and service reviews and ratings.
It is desirable to improve ratings-based feedback sorting and display for online transactions.